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In this paper, the covert communication system with the assistance of an active intelligent reflecting surface (IRS) is investigated. Unlike the conventional passive IRS, which reflects signals without amplification, the active IRS can jointly amplify the amplitude and adjust the phase of the reflected signals to overcome the multiplicative fading effect. However, the additional noise introduced by the active IRS is not conducive to the signal demodulation at the destination and increases the detection probability by the warder. To overcome this problem and maximize the covert rate of the system, we jointly design the transmission power at the transmitter and the reflection coefficient of each reflection element at the active IRS. Since the optimization variables are coupled in the objective function and the constraints, an efficient semi-definite relaxation combined alternating optimization algorithm is proposed to solve the non-convex problem, where each subproblem is solved optimally. Numerical results demonstrate that the active IRS assisted system outperforms the passive one in term of the covert rate even when the number of reflection elements is large (such as ten thousand of elements), since the active IRS can amplify the incident signal to overcome the multiplicative fading effect.

Residual hardware impairments widely exist in transceivers and intelligent reflecting surface (IRS) in practical systems, which lead to serious signal distortion, causing performance loss and covert transmission challenging. In this paper, we study the robust transmission design for an IRS-aided covert communication system in the presence of transceiver and IRS hardware impairments. To maximize the signal-to-noise ratio at the legitimate receiver and satisfy the covertness requirement, the transmit power at the source and the reflection coefficients at the IRS are jointly optimized. Since the optimization variables are coupled, an alternating optimization algorithm is proposed to solve the optimization problem. Specifically, in each iteration, the analytical expression of the optimal transmit power is obtained, and the penalty successive convex approximation algorithm is adopted to obtain the optimal reflection coefficients. Numerical results show the performance loss caused by hardware impairments. Besides, by comparing the values of Kullback-Leibler divergence, results also illustrate that the proposed transmission scheme is more robust to the hardware impairments, as the nonrobust designed parameters can not satisfy the covert constraint.